MarkUp Language Short Presentation - Exercise2

Min Wen Yang

A centered still figure

Tutu (My favorite character!)

an interactive table

An interactive figure

a two-column slide

Fang is a wolf that loves chairs!

Audie is another wolf that has a dream to be a model!

An aligned multi-row equation

\[\begin{aligned} f(x) &= x^2 + 2x + 1 \\ &= (x + 1)^2 \\ &= x^2 + 2x + 1 \end{aligned}\]

Citation

  1. Not every ML methods are fit to estimate \(O_i\) (e.g kNN)

  2. The data (area A and B) is imbalanced (He and Garcia 2009).

  3. There is a big overlap between units for model construction and units for estimation.

  4. Non-probability sampling has the feature of high efficiency and low cost.

  5. The inclusion mechanism of non-probability sampling is generally unknwon and could be selective (Spiegelhalter 2014).

Reference List

He, Haibo, and Edwardo A. Garcia. 2009. “Learning from Imbalanced Data.” IEEE Transactions on Knowledge and Data Engineering 21 (9): 1263–84. https://doi.org/10.1109/TKDE.2008.239.
Spiegelhalter, D. J. 2014. “The Future Lies in Uncertainty.” Science 345 (6194): 264–65. https://doi.org/10.1126/science.1251122.

Displayed-only R-code

set.seed(123)
data <- rnorm(100)
summary(data)

cached and labeled r-code

    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
-2.30917 -0.49385  0.06176  0.09041  0.69182  2.18733

r-code, executed, but not displayed (e.g. a figure generation)